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Returns expression for an 'average' single cell in each identity class
AverageExpression( object, assays = NULL, features = NULL, return.seurat = FALSE, add.ident = NULL, slot = "data", use.scale = FALSE, use.counts = FALSE, verbose = TRUE, ... )
Seurat object
Which assays to use. Default is all assays
Features to analyze. Default is all features in the assay
Whether to return the data as a Seurat object. Default is FALSE
Place an additional label on each cell prior to averaging (very useful if you want to observe cluster averages, separated by replicate, for example)
Slot to use; will be overriden by use.scale and use.counts
use.scale
use.counts
Use scaled values for feature expression
Use count values for feature expression
Print messages and show progress bar
Arguments to be passed to methods such as CreateSeuratObject
CreateSeuratObject
Returns a matrix with genes as rows, identity classes as columns. If return.seurat is TRUE, returns an object of class Seurat.
Seurat
Output is in log-space when return.seurat = TRUE, otherwise it's in non-log space. Averaging is done in non-log space.
return.seurat = TRUE
# NOT RUN { head(AverageExpression(object = pbmc_small)) # }
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